Control theory as a conceptual framework for intensive care monitoring

Diagnostic monitoring in anaesthesia using fuzzy trend templates for matching temporal patterns

A technique based on the concept of a 'fuzzy trend template' has been developed to identify characteristic patterns in multiple time-series. The method has its foundation in fuzzy logic and allows for the intuitive and transparent description of 'templates', which preserve nuances of vagueness, temporal relationships and quantitative descriptors. Evaluation of fuzzy trend templates can provide both belief and plausibility information for use in diagnostic applications. The technique has been applied to the diagnosis of specific problems in anaesthesia and has demonstrated sensitivity and specificity of 95 and 65%, respectively. Evaluation of fuzzy trend templates is, computationally, relatively efficient and has allowed a real-time implementation. The technique has the potential to be useful in any domain that requires temporal pattern recognition based on linguistic rules.

Decision support systems in diabetes: a systems perspective

This paper examines, from a systems perspective, some of the major issues associated with the provision of computer-based decision support in the management of the diabetic patient. The importance of understanding the underlying dynamics is emphasised, as is the value of a systems approach to the specification, design and evaluation of decision support systems if they are to find clinical acceptance.

NéoGanesh: a working system for the automated control of assisted ventilation in ICUs

Automating the control of therapy administered to a patient requires systems which integrate the knowledge of experienced physicians. This paper describes NéoGanesh, a knowledge-based system which controls, in closed-loop, the mechanical assistance provided to patients hospitalized in intensive care units. We report on how new advances in knowledge representation techniques have been used to model medical expertise. The clinical evaluation shows that such a system relieves the medical staff of routine tasks, improves patient care, and efficiently supports medical decisions regarding weaning. To be able to work in closed-loop and to be tested in real medical situations, NéoGanesh deals with a voluntarily limited problem. However, embedded in a powerful distributed environment, it is intended to support future extensions and refinements and to support reuse of knowledge bases.

THEMPO: a knowledge-based system for therapy planning in pediatric oncology

This article describes the knowledge-based system THEMPO (Therapy Management in Pediatric Oncology), which supports protocol-directed therapy planning and configuration in pediatric oncology. THEMPO provides a semantic network controlled by graph grammars to cover the different types of knowledge relevant in the domain, and offers a suite of acquisition tools for knowledge base authoring. Medical problem solvers, operating on the oncological network, reason about adequate therapeutic and diagnostic timetables for a patient. Furthermore, a corresponding patient record, also based on semantic networks and graph grammars, has been implemented to represent the course of therapy of an oncological patient.